Characterization of Brassica napus L. genotypes utilizing sequence-related amplified polymorphism and genotyping by sequencing in association with cluster analysis
Bibliographic record
Abstract
Identifying parental combinations that exhibit high heterosis is a constant target for commercial Brassica napus L. hybrid development programs. Finding high heterotic parental combinations can require hundreds of test crosses and years of yield evaluation. Heterotic pool development could be used to divide breeding material into specific breeding pools and focus the number of parental combinations created. Here, we report the genotypic characterization of 79 B. napus genotypes by calculating genetic distance based on sequence-related amplified polymorphism (SRAP) and genotyping by sequencing (GBS) in association with a neighbour-joining clustering algorithm. Despite the different genotypic analyses, neighbour-joining cluster analysis based on genetic distance of SRAP and GBS produced similar clusters. Homology between SRAP and GBS clusters was approximately 77 % when manually comparing clusters and 68 % when comparing clusters using Compare2Trees. This research demonstrates that SRAP can have similar efficacy when compared to next-generation sequencing technology for heterotic pool classification. This information may provide an important breeding scaffold for the development of hybrid cultivars based upon genetic distance and cluster analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".